# Kurtosis

Kurtosis : Kurtosis is a statistical measure that describes the shape of a distribution. It is defined as the degree of peakedness or flatness of a distribution relative to the normal distribution. There are two types of kurtosis: excess kurtosis and normal kurtosis. Excess kurtosis is a measure of the amount of peakedness or flatness […]

# Kubernetes (k8s)

Kubernetes (k8s) : Kubernetes, also known as k8s, is an open-source platform that is used to automate the deployment, scaling, and management of containerized applications. It is a popular choice for organizations that want to run their applications in the cloud or on-premises, as it provides a consistent and reliable way to manage and orchestrate […]

# Kruskal-Wallis test

Kruskal-Wallis test : The Kruskal-Wallis test is a non-parametric statistical test used to determine if there are significant differences among the median ranks of several groups. Unlike the parametric ANOVA test, which assumes a normal distribution of the data, the Kruskal-Wallis test does not assume any specific distribution of the data and can be used […]

# Kriging

Kriging : Kriging is a spatial interpolation technique used in geostatistics to estimate the value of a variable at a given location based on its observed values at neighboring locations. It is a type of spatial prediction that accounts for spatial autocorrelation, the tendency of nearby locations to have similar values, in order to provide […]

# K-Nearest Neighbors (KNN)

K-Nearest Neighbors (KNN) : K-Nearest Neighbors, or KNN, is a classification algorithm used in machine learning. It is a non-parametric and lazy learning algorithm, meaning it does not make any assumptions about the underlying data distribution and does not require any prior training. In KNN, the idea is to find the “k” nearest data points […]

# Knowledge discovery in data bases KDD

Knowledge discovery in data bases KDD : Knowledge discovery in databases (KDD) is the process of discovering useful information and patterns in data sets. It is a multidisciplinary field that uses techniques from statistics, machine learning, and data mining to extract knowledge from data. KDD involves several steps, including data cleaning and preprocessing, feature selection […]

# K-means inverse regression

K-means inverse regression : K-means inverse regression is a method of dimension reduction that is often used in data mining and machine learning. It is based on the idea of clustering data points into a set of K clusters, and then using inverse regression to map each cluster to a low-dimensional subspace. For example, consider […]

# K-Means

K-Means : K-means is a popular clustering algorithm that groups similar data points together into clusters. It is an iterative process that involves dividing a dataset into a specified number of clusters (K) and then assigning each data point to the cluster with the closest mean. For example, let’s say we have a dataset of […]

# Klotz test

Klotz test : The Klotz test is a statistical procedure that is used to determine whether two or more samples have equal variances. This test is commonly used in experimental research to assess the homogeneity of variances between different groups of subjects. One example of the Klotz test would be a study that compares the […]

# Kleiner-Hartigan trees

Kleiner-Hartigan trees : Kleiner-Hartigan trees, also known as K-H trees, are a type of data structure used to represent data sets in a hierarchical manner. They are named after the two researchers, William Kleiner and John Hartigan, who first proposed the concept in 1980. K-H trees are similar to other hierarchical data structures, such as […]